# production
標記為「production」的 21 篇文章
Defense-in-Depth Reference Architecture
Complete reference architecture for defense-in-depth LLM application security with implementation blueprints.
Prompt Injection in Production Systems
Real-world case studies of prompt injection exploits in production AI deployments, including attack timelines, impact analysis, and lessons learned.
Lab: Building a Production Red Team Harness
Build a full-featured, production-quality red team harness with multi-model support, async testing, structured result storage, and HTML reporting.
Production Environment Simulation Lab
Test attacks against a simulated production environment with realistic logging, monitoring, and alerting.
Training Data Extraction from Production LLMs
Implement Carlini et al.'s techniques to extract memorized training data from production language model APIs.
Lab: Defense Engineering Lab
Expert-level lab for building and evaluating a production-grade multi-layer AI defense system including input classifiers, output monitors, semantic analysis, and adversarial robustness testing.
Membership Inference Against Production LLMs
Implement membership inference attacks to determine whether specific data was used in training an LLM.
Continuous Red Teaming for Production AI Systems
Implementing ongoing, automated red teaming programs for AI systems in production environments.
Production Monitoring for LLM Security Events
Walkthrough for building production monitoring systems that detect LLM security events in real time, covering log collection, anomaly detection, alert configuration, dashboard design, and incident correlation.
LLM Guard Production Deployment Guide
Deploy LLM Guard in a production environment with custom scanners, performance optimization, and monitoring.
建構生產 AI 防禦堆疊
如何為生產部署建構分層 AI 防禦堆疊——涵蓋輸入過濾、輸出監控、護欄、異常偵測與事件應變整合。
防禦-in-Depth Reference Architecture
Complete reference architecture for defense-in-depth LLM application security with implementation blueprints.
提示詞注入 in Production Systems
Real-world case studies of prompt injection exploits in production AI deployments, including attack timelines, impact analysis, and lessons learned.
實驗室: Building a Production 紅隊 Harness
Build a full-featured, production-quality red team harness with multi-model support, async testing, structured result storage, and HTML reporting.
Production Environment Simulation 實驗室
Test attacks against a simulated production environment with realistic logging, monitoring, and alerting.
訓練 Data Extraction from Production LLMs
Implement Carlini et al.'s techniques to extract memorized training data from production language model APIs.
實驗室: 防禦 Engineering 實驗室
專家-level lab for building and evaluating a production-grade multi-layer AI defense system including input classifiers, output monitors, semantic analysis, and adversarial robustness testing.
Membership Inference Against Production LLMs
Implement membership inference attacks to determine whether specific data was used in training an LLM.
Continuous 紅隊演練 for Production AI Systems
Implementing ongoing, automated red teaming programs for AI systems in production environments.
Production Monitoring for LLM 安全 Events
導覽 for building production monitoring systems that detect LLM security events in real time, covering log collection, anomaly detection, alert configuration, dashboard design, and incident correlation.
LLM Guard Production Deployment 指南
Deploy LLM Guard in a production environment with custom scanners, performance optimization, and monitoring.